Literature DB >> 21447820

Nuclear origins of cell-to-cell variability.

Z Waks1, P A Silver.   

Abstract

During the past decade, it has become increasingly evident that there is variation in the transcriptome of genetically identical cells, even when grown in homogenous environments. This cell-to-cell variability has been shown to have a central role in processes ranging from stem cell differentiation to chemotherapy resistance. Given that many genes display extensive heterogeneity in their messenger RNA (mRNA) abundance on a per cell basis, understanding the nuclear sources of this variability is important for our fundamental grasp of nuclear function and stands to have clinical manifestations. In this chapter, we assess the contribution of different transcription regimes, nuclear architecture dynamics, RNA polymerase elongation, and gene copy number to transcriptome heterogeneity. We also discuss techniques that can be used to quantify single-cell mRNA abundance and conclude by commenting on future research directions.

Mesh:

Year:  2011        PMID: 21447820     DOI: 10.1101/sqb.2010.75.027

Source DB:  PubMed          Journal:  Cold Spring Harb Symp Quant Biol        ISSN: 0091-7451


  7 in total

1.  Transcriptional and translational heterogeneity among neonatal mouse spermatogonia.

Authors:  Brian P Hermann; Kazadi N Mutoji; Ellen K Velte; Daijin Ko; Jon M Oatley; Christopher B Geyer; John R McCarrey
Journal:  Biol Reprod       Date:  2015-01-07       Impact factor: 4.285

2.  Conceptualizing a tool to optimize therapy based on dynamic heterogeneity.

Authors:  David Liao; Luis Estévez-Salmerón; Thea D Tlsty
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

3.  Generalized principles of stochasticity can be used to control dynamic heterogeneity.

Authors:  David Liao; Luis Estévez-Salmerón; Thea D Tlsty
Journal:  Phys Biol       Date:  2012-11-29       Impact factor: 2.583

4.  Rapid identification of mRNA processing defects with a novel single-cell yeast reporter.

Authors:  Matthew R Sorenson; Scott W Stevens
Journal:  RNA       Date:  2014-03-26       Impact factor: 4.942

5.  Microfluidic probe for single-cell analysis in adherent tissue culture.

Authors:  Aniruddh Sarkar; Sarah Kolitz; Douglas A Lauffenburger; Jongyoon Han
Journal:  Nat Commun       Date:  2014-03-05       Impact factor: 14.919

6.  Combined model of intrinsic and extrinsic variability for computational network design with application to synthetic biology.

Authors:  Tina Toni; Bruce Tidor
Journal:  PLoS Comput Biol       Date:  2013-03-28       Impact factor: 4.475

7.  Toward uncharted territory of cellular heterogeneity: advances and applications of single-cell RNA-seq.

Authors:  Brandon Lieberman; Meena Kusi; Chia-Nung Hung; Chih-Wei Chou; Ning He; Yen-Yi Ho; Josephine A Taverna; Tim H M Huang; Chun-Liang Chen
Journal:  J Transl Genet Genom       Date:  2021-01-01
  7 in total

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